Mixed-domain negatives.
Different from previous next-item prediction models that use in-domain negatives [1]}, [2]}, we adopt mixed-domain items as negatives for enhancing the multi-domain fusion during pre-training. Due to efficiency concerns, we directly use the in-batch items as negatives (i.e., the \(B-1\)  ground-truth items paired with other sequential contexts).
Since we construct the batch by sampling from multiple domains,
in-batch sampling can naturally generate mixed-domain negatives.
